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The human factor in licensing and operating the next generation of nuclear plants
As human factors specialists working at the intersection of human performance and nuclear operations, we are witnessing one of the nuclear sector’s most significant transitions in decades. The emergence of small modular reactors, microreactors, and other advanced designs is reshaping the industry’s landscape. Digital instrumentation and controls, passive safety systems, and increased automation are creating opportunities for greater safety margins and more flexible operation. These same features also fundamentally redefine what it means to “operate” a nuclear plant. Interactions among human roles, automation, and passive systems shape how people maintain awareness, exercise judgment, and intervene when necessary. These developments affect both operational realities and the regulatory foundations on which nuclear safety is built.
Tomasz Skorek
Nuclear Technology | Volume 205 | Number 12 | December 2019 | Pages 1540-1553
Technical Paper | doi.org/10.1080/00295450.2019.1580532
Articles are hosted by Taylor and Francis Online.
The input uncertainties propagation methods are the most frequently applied statistical methods in uncertainty analyses. Among them, particularly popular are the methods based on Wilks’ formula. Numerous studies on uncertainty analyses show that the identification and quantification of input uncertainties is a major problem with uncertainty analyses. Among input uncertainties evaluation, the identification and quantification of physical model uncertainties in thermal-hydraulic codes appear to be particularly difficult.
This paper deals with this problem by proposing inherent model uncertainties quantification by code developers in the frame of code development and validation. The introduction of the extended code validation would not only contribute to potential uncertainty analyses, solving to a large degree the problem of model uncertainties quantification, but also contribute to code validation, and as a consequence, improve the safety issues. A not-negligible factor is also better management of the resources. Instead of uncertainty quantification repeatedly performed by each user, the quantification could be performed once and, in addition, by experts having the required know-how.
Introducing this new standard in code validation would require additional effort from the code developers but integral quantification of the model uncertainties would be profitable also for code development. In fact, by code development, in particular if the model is own development of the team, such an accuracy (or uncertainty) evaluation is usually performed. The additional effort, in this case, would be to describe the present information in the form of probability distribution functions or at least in the form of ranges.